3 papers
cs.LG2026
Recursive Offline Distillation via Entropy Gain Sampling and Answer Mixing
Andrey Goncharov, Daniil Vyazhev, Simon Epanov +1
Distillation of reasoning chains from Large Language Models (LLMs) into their smaller siblings is a standard training approach. Frequently, researchers do not have full access to a…
cs.LG2025
Complexity-aware fine-tuning
Andrey Goncharov, Daniil Vyazhev, Petr Sychev +2
General-purpose Large Language Models (LLMs) are frequently fine-tuned through supervised fine-tuning (SFT) to enhance performance in specific domains. Better results can be achiev…
cs.CL2025
When an LLM is apprehensive about its answers -- and when its uncertainty is justified
Petr Sychev, Andrey Goncharov, Daniil Vyazhev +2
Uncertainty estimation is crucial for evaluating Large Language Models (LLMs), particularly in high-stakes domains where incorrect answers result in significant consequences. Numer…